Poster + Presentation + Paper
10 October 2020 Research on a line-expanded visual odometry in dynamic environment
Author Affiliations +
Conference Poster
Abstract
The Point feature and line feature have been widely used in visual SLAM(simultaneous localization and mapping) algorithm. But most of these methods assume that the environments are static, ignoring that there are often dynamic objects in real world, which can degrade the SLAM performance. In order to solve this problem, a line-expanded visual odometry is proposed. It calculates optical flow between two adjacent frames to identify and eliminate dynamic point features in dynamic objects, and use the rest of point features to find the collinear relationship to expand line features for visual SLAM algorithm based on point features. Final it use the rest of point features and line features to estimate the camera pose. The proposed method not only reduces the influence of dynamic objects, but also avoids the tracking failure caused by few point features. The experiments are carried out on a TUM dataset. Compared with state-of-the-art methods like ORB (oriented FAST and rotated BRIEF) method and ORB add optical flow method, the results demonstrate that the proposed method reduces the tracking error and improve the robustness and accuracy of visual odometry in dynamic environments.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhang-Fang Hu, Yong Yang, and Yuan Luo "Research on a line-expanded visual odometry in dynamic environment", Proc. SPIE 11550, Optoelectronic Imaging and Multimedia Technology VII, 1155017 (10 October 2020); https://doi.org/10.1117/12.2574361
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Visualization

Optical flow

Cameras

Detection and tracking algorithms

Failure analysis

Optical tracking

RELATED CONTENT

SDG SLAM an improved visual semantic SLAM algorithm towards...
Proceedings of SPIE (September 13 2024)
Use of multiple visual features for object tracking
Proceedings of SPIE (December 28 1998)
Real-time tracking of people using stereo and motion
Proceedings of SPIE (March 11 1994)
A phantom design for validating colonoscopy tracking
Proceedings of SPIE (February 23 2012)
Object tracking in real environments
Proceedings of SPIE (September 07 2010)

Back to Top